( ✦﹏✦） รีทวีตแล้ว
GEPA <1 years old 😮
incredible the impact that the ideas here have spawned on hill climbing + improving agents
does anyone know of cool work on looping/GEPA/Optimize_Anything + RL?
main ideas:
- eventually harness opt hits the wall of model intelligence
- we can break through that wall by RLing on good evals that increase model ability in the eval domains
- new weights shape intelligence where an updated harness can better use these new weights
- loop
Model-Harness codesign is really interesting, we’re pushing here much more with using traces to create datasets for self-improvement
and there’s some interesting work to do in marrying Harness Eng and RL recipes here 👀
Lakshya A Agrawal@LakshyAAAgrawal
How does prompt optimization compare to RL algos like GRPO? GRPO needs 1000s of rollouts, but humans can learn from a few trials—by reflecting on what worked & what didn't. Meet GEPA: a reflective prompt optimizer that can outperform GRPO by up to 20% with 35x fewer rollouts!🧵
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